543 resultados para real world context
Resumo:
We introduce Kamouflage: a new architecture for building theft-resistant password managers. An attacker who steals a laptop or cell phone with a Kamouflage-based password manager is forced to carry out a considerable amount of online work before obtaining any user credentials. We implemented our proposal as a replacement for the built-in Firefox password manager, and provide performance measurements and the results from experiments with large real-world password sets to evaluate the feasibility and effectiveness of our approach. Kamouflage is well suited to become a standard architecture for password managers on mobile devices.
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We revisit the venerable question of access credentials management, which concerns the techniques that we, humans with limited memory, must employ to safeguard our various access keys and tokens in a connected world. Although many existing solutions can be employed to protect a long secret using a short password, those solutions typically require certain assumptions on the distribution of the secret and/or the password, and are helpful against only a subset of the possible attackers. After briefly reviewing a variety of approaches, we propose a user-centric comprehensive model to capture the possible threats posed by online and offline attackers, from the outside and the inside, against the security of both the plaintext and the password. We then propose a few very simple protocols, adapted from the Ford-Kaliski server-assisted password generator and the Boldyreva unique blind signature in particular, that provide the best protection against all kinds of threats, for all distributions of secrets. We also quantify the concrete security of our approach in terms of online and offline password guesses made by outsiders and insiders, in the random-oracle model. The main contribution of this paper lies not in the technical novelty of the proposed solution, but in the identification of the problem and its model. Our results have an immediate and practical application for the real world: they show how to implement single-sign-on stateless roaming authentication for the internet, in a ad-hoc user-driven fashion that requires no change to protocols or infrastructure.
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In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.
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Motivation Awareness is an integral part of remote collaborative work and has been an important theme within the CSCW research. Our project aims at understanding and mediating non-verbal cues between remote participants involved in a design project. Research approach Within the AMIDA project we focus on distributed 'cooperative design' teams. We especially focus on the 'material' signals - signals in which people communicate through material artefacts, locations and their embodied actions. We apply an ethnographic approach to understand the role of physical artefacts in co-located naturalistic design setting. Based on the results we will generate important implications to support remote design work. We plan to develop a mixed-reality interface supported by a shared awareness display. This awareness display will provide information about the activities happening in the design room to remotely located participants. Findings/Design Our preliminary investigation with real-world design teams suggests that both the materiality of designers' work settings and their social practices play an important role in understanding these material signals that are at play. Originality/Value Most research supporting computer mediated communication have focused on either face-to-face or linguistically oriented communication paradigms. Our research focuses on mediating the non-verbal, material cues for supporting collaborative activities without impoverishing what designers do in their day to day working lives. Take away message An ethnographic approach allows us to understand the naturalistic practices of design teams, which can lead to designing effective technologies to support group work. In that respect, the findings of our research will have a generic value beyond the application domain chosen (design teams).
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Background The learning and teaching of epidemiology is core to many public health programs. Many students find the content of epidemiology, and specifically risk of bias assessment, challenging to learn. Howbeit, learning is enhanced when knowledge is able to be acquired from an active-learning, hands-on experience. Methods The innovative use of wireless audience response technology “clickers” was incorporated into the lectures of the university’s post-graduate epidemiology units and the tailored epidemiological modules delivered for professional disciplines (e.g. optometry). Clickers were used to apply several pedagogical approaches of active learning including peer-instruction and real-world simulation. Students were also assessed for their gain in knowledge within the lecture (pre-post) and their perceptions of how the use of clickers helped them learn. The routine university-wide end of semester Insight Survey provided further information of the student’s satisfaction with the approach. Results The technology was useful in identifying deficits of knowledge of key concepts either before or after instruction. Where key concepts were re-tested post-lecture, as expected, knowledge increased significantly and provided immediate feed-back to students. Across the lecture series, typically 85% of students identified the technology helped them learn, increased their opportunity to interact with the lecturer, and recommend their use for future classes. The Insight Survey report identified 93% of respondents identified the unit in which clickers were consistently used provided good learning opportunities. Numerous student comments supported the teaching method. Conclusions Epidemiological subject matter lends itself to incorporation of audience response technology. The use of the technology to facilitate interactive voting provides an instant response and participation of everyone to enhance the classroom experience. The pedagogical approach increases students’ knowledge and increases their satisfaction with the unit.
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Software development settings provide a great opportunity for CSCW researchers to study collaborative work. In this paper, we explore a specific work practice called bug reproduction that is a part of the software bug-fixing process. Bug re-production is a highly collaborative process by which software developers attempt to locally replicate the ‘environment’ within which a bug was originally encountered. Customers, who encounter bugs in their everyday use of systems, play an important role in bug reproduction as they provide useful information to developers, in the form of steps for reproduction, software screenshots, trace logs, and other ways to describe a problem. Bug reproduction, however, poses major hurdles in software maintenance as it is often challenging to replicate the contextual aspects that are at play at the customers’ end. To study the bug reproduction process from a human-centered perspective, we carried out an ethnographic study at a multinational engineering company. Using semi-structured interviews, a questionnaire and half-a-day observation of sixteen software developers working on different software maintenance projects, we studied bug reproduction. In this pa-per, we present a holistic view of bug reproduction practices from a real-world set-ting and discuss implications for designing tools to address the challenges developers face during bug reproduction.
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Studies of experimental grassland communities have demonstrated that plant diversity can stabilize productivity through species asynchrony, in which decreases in the biomass of some species are compensated for by increases in others. However, it remains unknown whether these findings are relevant to natural ecosystems, especially those for which species diversity is threatened by anthropogenic global change. Here we analyse diversity-stability relationships from 41 grasslands on five continents and examine how these relationships are affected by chronic fertilization, one of the strongest drivers of species loss globally. Unmanipulated communities with more species had greater species asynchrony, resulting in more stable biomass production, generalizing a result from biodiversity experiments to real-world grasslands. However, fertilization weakened the positive effect of diversity on stability. Contrary to expectations, this was not due to species loss after eutrophication but rather to an increase in the temporal variation of productivity in combination with a decrease in species asynchrony in diverse communities. Our results demonstrate separate and synergistic effects of diversity and eutrophication on stability, emphasizing the need to understand how drivers of global change interactively affect the reliable provisioning of ecosystem services in real-world systems.
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Addressing the Crew Scheduling Problem (CSP) in transportation systems can be too complex to capture all details. The designed models usually ignore or simplify features which are difficult to formulate. This paper proposes an alternative formulation using a Mixed Integer Programming (MIP) approach to the problem. The optimisation model integrates the two phases of pairing generation and pairing optimisation by simultaneously sequencing trips into feasible duties and minimising total elapsed time of any duty. Crew scheduling constraints in which the crew have to return to their home depot at the end of the shift are included in the model. The flexibility of this model comes in the inclusion of the time interval of relief opportunities, allowing the crew to be relieved during a finite time interval. This will enhance the robustness of the schedule and provide a better representation of real-world conditions.
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Understanding the key factors that influence the evidentiary basis for practice and using skills in retrieving evidence that informs practice change are essential to the development of a health professional's career, regardless of the discipline. This chapter focuses on the key links between research and practice, particularly how health professionals use various sources of evidence and new knowledge to inform and improve the effectiveness of their practice in order to benefit the health of clients. Evidence-based practice and research utilisation are two major global research/practice initiatives that form the basis for this chapter. Examples that illustrate the real-world application of these initiatives are included in the Research Alive and Case Study sections. How practice change can be facilitated within health organisations is also briefly introduced.
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This study explores people's risk taking behaviour after having suffered large real-world losses following a natural disaster. Using the margins of the 2011 Australian floods (Brisbane) as a natural experimental setting, we find that homeowners who were victims of the floods and face large losses in property values are 50% more likely to opt for a risky gamble -- a scratch card giving a small chance of a large gain ($500,000) -- than for a sure amount of comparable value ($10). This finding is consistent with prospect theory predictions regarding the adoption of a risk-seeking attitude after a loss.
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This is an exploratory study into the effective use of embedding custom made audiovisual case studies (AVCS) in enhancing the student’s learning experience. This paper describes a project that used AVCS for a large divergent cohort of undergraduate students, enrolled in an International Business course. The study makes a number of key contributions to advancing learning and teaching within the discipline. AVCS provide first hand reporting of the case material, where the students have the ability to improve their understanding from both verbal and nonverbal cues. The paper demonstrates how AVCS can be embedded in a student-centred teaching approach to capture the students’ interest and to enhance a deep approach to learning by providing real-world authentic experience.
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Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.
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Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.
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Business processes are an important instrument for understanding and improving how companies provide goods and services to customers. Therefore, many companies have documented their business processes well, often in the Event-driven Process Chains (EPC). Unfortunately, in many cases the resulting EPCs are rather complex, so that the overall process logic is hidden in low level process details. This paper proposes abstraction mechanisms for process models that aim to reduce their complexity, while keeping the overall process structure. We assume that functions are marked with efforts and splits are marked with probabilities. This information is used to separate important process parts from less important ones. Real world process models are used to validate the approach.
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Behavioral models capture operational principles of real-world or designed systems. Formally, each behavioral model defines the state space of a system, i.e., its states and the principles of state transitions. Such a model is the basis for analysis of the system’s properties. In practice, state spaces of systems are immense, which results in huge computational complexity for their analysis. Behavioral models are typically described as executable graphs, whose execution semantics encodes a state space. The structure theory of behavioral models studies the relations between the structure of a model and the properties of its state space. In this article, we use the connectivity property of graphs to achieve an efficient and extensive discovery of the compositional structure of behavioral models; behavioral models get stepwise decomposed into components with clear structural characteristics and inter-component relations. At each decomposition step, the discovered compositional structure of a model is used for reasoning on properties of the whole state space of the system. The approach is exemplified by means of a concrete behavioral model and verification criterion. That is, we analyze workflow nets, a well-established tool for modeling behavior of distributed systems, with respect to the soundness property, a basic correctness property of workflow nets. Stepwise verification allows the detection of violations of the soundness property by inspecting small portions of a model, thereby considerably reducing the amount of work to be done to perform soundness checks. Besides formal results, we also report on findings from applying our approach to an industry model collection.